Instructions to use adammandic87/032cbbb5-bf71-40df-bff5-a79fb44167c5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use adammandic87/032cbbb5-bf71-40df-bff5-a79fb44167c5 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Orenguteng/Llama-3-8B-Lexi-Uncensored") model = PeftModel.from_pretrained(base_model, "adammandic87/032cbbb5-bf71-40df-bff5-a79fb44167c5") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/scheduler.pt from adammandic87/032cbbb5-bf71-40df-bff5-a79fb44167c5: direct link, hf CLI and curl.
- Browser
- Download file 1.06 kB
-
https://huggingface.co/adammandic87/032cbbb5-bf71-40df-bff5-a79fb44167c5/resolve/main/last-checkpoint/scheduler.pt
- Command line
-
hf download hf://adammandic87/032cbbb5-bf71-40df-bff5-a79fb44167c5/last-checkpoint/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/adammandic87/032cbbb5-bf71-40df-bff5-a79fb44167c5/resolve/main/last-checkpoint/scheduler.pt
1.06 kB
- Xet hash:
- adeb24deb76b2eb848bf71dc0260caea897cb5fc7096e5a03b24f8bf056074b8
- Size of remote file:
- 1.06 kB
- SHA256:
- b1df0528620c07325b8faa7567e59b0c1e86a1f1ee6af1245a69c6c0463fe4e2
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